Submissions to the new Datasets and Benchmarks track require data documentation and availability on an open repository.

Organizers of the NeurIPS 2021 conference recently announced a new track for Datasets and Benchmarks. This is a significant development for a major machine learning (ML) conference to highlight the importance of data in developing algorithms for real-world problems. We at Radiant Earth Foundation welcome this initiative and applaud the organizers for establishing this new track.

In recent years, there have been many discussions and arguments to incentive ML researchers to work on real-world problems. One of those incentive mechanisms is the opportunity to publish a paper in a peer-reviewed conference, and getting recognition for working on these problems. …


STAC specification is getting closer to the ver 1.0 milestone, and as such the first virtual Cloud Native Geospatial Sprint is being organized next week. An outreach day is planned on Sep 8th with a series of talks and tutorials for everyone. Read more about the sprint in this blog post by our Technology Fellow Chris Holmes. A new addition to the sprint is a data labeling contest!

If you have followed our blogs, we have written many times on the importance of open-access and high-quality labels on satellite imagery for building geospatial machine learning models. …


Thinking that having familiarity with Las Vegas in the United States would be enough to navigate the streets of Khartoum, Sudan sounds far-fetched. Yet, many machine learning models use Western-centric training data to predict features from satellite imagery in places as culturally and economically diverse as Bangladesh, Uganda, or Honduras.

Advances in computer vision and machine learning (ML) are improving the ability to accurately extract insights from frequent and high-resolution satellite imagery, shedding light on global development and progress toward Sustainable Development Goals. …


Advances in sensor technology, cloud computing, and machine learning (ML) continue to converge to accelerate innovation in the field of remote sensing. However, fundamental tools and technologies still need to be developed to drive further breakthroughs and to ensure that the Global Development Community (GDC) reaps the same benefits that the commercial marketplace is experiencing. This process requires us to take a collaborative approach.

Data collaborative innovation — that is, a group of actors from different data domains working together toward common goals — might hold the key to finding solutions for some of the global challenges that the world…

Hamed Alemohammad

Chief Data Scientist & Exec Director @ Radiant Earth Foundation

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